Dataset Information

Alcohol consumption and obesity: The hidden scare with COVID-19 severity.

ABSTRACT: Obese individuals seem to be at the highest risk of contracting COVID-19 infection. Furthermore, severity of morbidity and mortality rates are higher in the developed world as compared to the developing world. One probable reason for this difference could be the difference in living conditions and exposure to other infections. Secondly, the difference in food especially, alcohol use may have deteriorating effects superimposed with obesity. Our hypothesis suggests that a combination of alcohol consumption and obesity causes low immunity and makes the individual prone to develop 'cytokine storm' and 'acute respiratory distress syndrome'; the hallmark of COVID-19 mortality and morbidity. Thus, we propose that reducing any one trigger can have a beneficial effect in combating the disease severity.

SUBMITTER: Bilal B

PROVIDER: S-EPMC7492811 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Alcohol consumption and obesity: The hidden scare with COVID-19 severity.

Bilal Bushra B Saleem Faizan F Fatima Syeda Sadia SS

Medical hypotheses 20200916

Obese individuals seem to be at the highest risk of contracting COVID-19 infection. Furthermore, severity of morbidity and mortality rates are higher in the developed world as compared to the developing world. One probable reason for this difference could be the difference in living conditions and exposure to other infections. Secondly, the difference in food especially, alcohol use may have deteriorating effects superimposed with obesity. Our hypothesis suggests that a combination of alcohol co ...[more]

PMID: 33254576

Similar Datasets

Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

Dataset Information

Alcohol consumption and obesity: The hidden scare with COVID-19 severity.

Publications

Alcohol consumption and obesity: The hidden scare with COVID-19 severity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets